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dc.contributor.authorWang, J.
dc.contributor.authorCao, Y.
dc.contributor.authorLiu, Keyu
dc.contributor.authorLiu, J.
dc.contributor.authorKashif, M.
dc.date.accessioned2017-04-28T13:59:33Z
dc.date.available2017-04-28T13:59:33Z
dc.date.created2017-04-28T09:06:08Z
dc.date.issued2017
dc.identifier.citationWang, J. and Cao, Y. and Liu, K. and Liu, J. and Kashif, M. 2017. Identification of sedimentary-diagenetic facies and reservoir porosity and permeability prediction: An example from the Eocene beach-bar sandstone in the Dongying Depression, China. Marine and Petroleum Geology. 82: pp. 69-84.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/52675
dc.identifier.doi10.1016/j.marpetgeo.2017.02.004
dc.description.abstract

Accurate prediction of reservoir porosity and permeability is essential for prospecting hydrocarbon reserves and petroleum production capacity. We propose an innovative reservoir porosity and permeability prediction method through identifying sedimentary-diagenetic facies, determining the porosity-permeability trends using core measurement data, extrapolating the spatial distribution of the sedimentary-diagenetic facies using log data through the Bayes discriminant analysis and predicting the reservoir porosity and permeability. The essence of the method was illustrated and its effectiveness was demonstrated using the Eocene beach-bar sandstones in the Dongying Depression, Bohai Bay Basin, eastern China. The Eocene beach bar sandstones are classified into fine sandstone, siltstone, and argillaceous siltstone based on grain sizes, sorting, and matrix contents. The major diagenetic processes that influence the porosity and permeability of the beach-bar sandstones are compaction, carbonate cementation and feldspar dissolution. Seven sedimentary-diagenetic facies were identified in the beach-bar sandstones based on the lithological types, and their corresponding diagenesis and influence extent on reservoir properties. The variation ranges of porosity and permeability (log K) of these sedimentary-diagenetic facies are typically less than 6% and 1.2, respectively. Both the porosity and permeability have well defined functional relationships with depth. The sedimentary-diagenetic facies can be identified effectively from logging data through the use of the Bayes discriminant analysis and corresponding cross-plots. The porosity and permeability (log K) of the well evaluated in the study were predicted with errors in the range of ±3% and ±0.6, respectively, based on the distribution and the fitting equation of the trend lines for the seven sedimentary-diagenetic facies. The predicted porosities and permeability of sedimentary-diagenetic facies match the measured porosities and permeability well.

dc.publisherElsevier
dc.titleIdentification of sedimentary-diagenetic facies and reservoir porosity and permeability prediction: An example from the Eocene beach-bar sandstone in the Dongying Depression, China
dc.typeJournal Article
dcterms.source.volume82
dcterms.source.startPage69
dcterms.source.endPage84
dcterms.source.issn0264-8172
dcterms.source.titleMarine and Petroleum Geology
curtin.departmentDepartment of Chemical Engineering
curtin.accessStatusFulltext not available


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